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Python Pandas: How to calculate 1st and 3rd quartiles?

Given a Pandas DataFrame, we have to calculate 1st and 3rd quartiles. By Pranit Sharma Last updated : September 25, 2023

Pandas is a special tool that allows us to perform complex manipulations of data effectively and efficiently. Inside pandas, we mostly deal with a dataset in the form of DataFrame. DataFrames are 2-dimensional data structures in pandas. DataFrames consist of rows, columns, and data.

Pandas consist of almost every kind of logical and mathematical operation. It allows us to calculate different statistical expressions from the DataFrame.

Quantiles are the set of values that is divided into equal-sized and equal-frequency subgroups.

Problem statement

Here, we will learn to calculate 1st and 3rd quantiles in a DataFrame. The quantiles are usually divided into a sub-group of 25%, 50%, and 75%.

Calculating 1st and 3rd quartiles in Pandas DataFrame

Pandas have a method called quantile() which takes a list of all the quantiles we want as an argument. We pass the quantiles in decimal form, for instance, 25% will be passed as 0.25. This method returns values at the given quantile over requested axis.

Let us understand with the help of an example,

Python program to calculate 1st and 3rd quartiles

# Importing pandas package
import pandas as pd

# Creating a Dictionary
data = {
    'Profit':[0.2544,0.332233,0.24323,0.58765,0.68576,0.43749],
    'Loss':[0.0121,0.0023123,0.012231,0.22323,0.000021,0.0312321]
}

# Creating a DataFrame
df = pd.DataFrame(data)

# Display DataFrame
print("Original DataFrame:\n",df,"\n")

# Calculating quantiles
result = df.Profit.quantile([0.25,0.5,0.75])

# Display result
print("Result:\n",result)

Output

The output of the above program is:

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